通过根据另一列中的条件更改一列中的值返回错误

Question

有一个df

request_type start_date  end_date

main         2020-02-12  2020-02-12

main         2020-02-12  2020-02-12

main         2020-02-12  2020-02-12

meta         2020-02-10  2020-02-10

meta         2020-02-10  2020-02-10

如果 request_type 是 main，我需要将“00:00:00”添加到 start_date 和 end_date 列的值

我尝试的是

df['start_date'] = np.where(df.request_type == 'main', df.start_date + ' 00:00:00', df.start_date)

我收到了这个错误

TypeError: unsupported operand type(s) for +: 'datetime.date' and 'str'

那好吧

df['start_date'] = np.where(df.request_type == 'main', df.start_date.dt.strftime('%Y-%m-%d') + ' 00:00:00', df.start_date)

然后我收到了这个错误

AttributeError: Can only use .dt accessor with datetimelike values

然后我检查了 start_date 列的类型，它是一个对象

我不知道哪里有错误以及如何解决它

感谢任何帮助

我的理想结果是

request_type start_date           end_date

main         2020-02-12 00:00:00  2020-02-12 00:00:00

main         2020-02-12 00:00:00  2020-02-12 00:00:00

main         2020-02-12 00:00:00  2020-02-12 00:00:00

meta         2020-02-10           2020-02-10

meta         2020-02-10           2020-02-10

Answer 1

这是可能的，但是得到混合值 - 在一列中带有和 python 日期对象的字符串00:00:00，所以接下来的处理应该是有问题的：df['start_date'] = np.where(df.request_type == 'main',&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; pd.to_datetime(df.start_date).dt.strftime('%Y-%m-%d 00:00:00'),&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; df.start_date)或者：df['start_date'] = np.where(df.request_type == 'main',&nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; df.start_date.astype(str) +' 00:00:00',&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; df.start_date)print (df)&nbsp; request_type&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;start_date&nbsp; &nbsp; end_date0&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main&nbsp; 2020-02-12 00:00:00&nbsp; 2020-02-121&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main&nbsp; 2020-02-12 00:00:00&nbsp; 2020-02-122&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main&nbsp; 2020-02-12 00:00:00&nbsp; 2020-02-123&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;meta&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;2020-02-10&nbsp; 2020-02-104&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;meta&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;2020-02-10&nbsp; 2020-02-10print (df['start_date'].apply(type))0&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <class 'str'>1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <class 'str'>2&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <class 'str'>3&nbsp; &nbsp; <class 'datetime.date'>4&nbsp; &nbsp; <class 'datetime.date'>Name: start_date, dtype: object